Skip to main content
USGS - science for a changing world

Near-Surface Permafrost Distribution Mapping Using Logistic Regression and Remote Sensing in Interior Alaska

Dates

Year
2012

Citation

Panda, Santosh K., Prakash, Anupma, Jorgenson, M. Torre, and Solie, Diana N., 2012, Near-Surface Permafrost Distribution Mapping Using Logistic Regression and Remote Sensing in Interior Alaska: GIScience & Remote Sensing, v. 49, no. 3, p. 346-363.

Summary

A combination of binary logistic regression (BLR) and remote sensing techniques was used to generate a high-resolution spatially continuous near-surface (< 1.6 m) permafrost map. The BLR model was used to establish the relationship between vegetation type, aspect-slope, and permafrost presence; it predicted permafrost presence with an accuracy of 88%. Near-surface permafrost occupies 45% of the total vegetated area and 37% of the total study area. As less than 50% of the study area is underlain by near-surface permafrost, this distribution is characterized as "sporadic" for the study area.; A combination of binary logistic regression (BLR) and remote sensing techniques was used to generate a high-resolution spatially continuous near-surface [...]

Contacts

Tags

Provenance

Data source
File Processing
File Process
Type
End Note
Reference Item
3397 record import test
Reference File
NWBLCC-20160406.xml

Additional Information

Identifiers

Type Scheme Key
DOI http://sciencebase.gov/vocab/identifierScheme 10.2747/1548-1603.49.3.346; 22 10.2747/1548-1603.49.3.346
ISSN http://sciencebase.gov/vocab/identifierScheme 1548-1603

Citation Extension

journalGIScience & Remote Sensing
parts
typeNotes
value11491
typePages
value346-363
typeVolume
value49
typeNumber
value3
citationTypeJournal Article

Item Actions

View Item as ...

Save Item as ...

View Item...